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One of the notable things about MIT’s computer science curriculum, at least back when I was studying there, was that you didn’t learn any “practical” programming languages. Our work was all done in either Scheme (a dialect of Lisp) or in CLU (an early object-oriented language). I can’t say that I have too many memories, let alone fond ones, of CLU. But I definitely drank the Kool-Aid about Lisp, and have long believed that it has always represented the pinnacle of programming languages. Things that I learned long ago in Lisp are only now becoming standard in popular languages.

For example, functional programming has become increasingly popular in the last few years, for a variety of reasons including the shrinking effects of Moore’s Law — and the resulting need to have multiple, immutable copies of your data in the computer, distributed across multiple processors. Lisp has long had many functional capabilities; it was Lisp that first introduced me to such functions as “map”, which I use multiple times each day. However, my regular uses of “map” are rarely in Lisp; rather, they’re in Python and Ruby, the languages that I use most in my day-to-day work.

When I teach classes in Ruby and Python, I spend a fair amount of time talking about functional programming techniques. It might sound funny to discuss functional programming in two languages that are so clearly object-oriented, but I actually find it quite natural. Sure, I create classes and throw objects around. But if I have an array of values, then it’s very fast and easy for me to process them with functional techniques. Python’s list comprehensions have basically taken the place of the “map” and “filter” functions, so while those exist, they’re not as necessary any more. But once you understand such functions as “map” and “filter”, you’re poised to do all sorts of amazing things.

Perhaps the most intriguing of the functions from this school is “reduce”. I have found, consistently over time, that “reduce” is the function most likely to surprise and confuse newcomers to this type of programming. That’s because it’s easy to confuse what “reduce” is doing, and to forget how flexible its output can be.

I’ve thus decided to write a series of blog posts about “reduce”, in both Python and Ruby. I’ll start with the simple stuff, and then move ahead with increasingly complex tasks. You won’t necessarily start to use “reduce” all of the time, but if you’re like me, you will find all sorts of interesting uses for it. I tell people that I tend to use “reduce” about once every six months — but when I do use it, it really saves the day.

In Ruby, we can use the “reduce” method (also available as “inject”, to satisfy people from the Smalltalk world) on any enumerable object. The invocation looks like this:

[1,2,3,4,5].reduce(0) {|a, b| a+b}

I’ll explain what this all means in a moment. But the most important change that I can already make is to use better names for the block parameters:

[1,2,3,4,5].reduce(0) {|total, current| total+current}

Ruby goes through each element of the enumerable, invoking the block on each element. Described in this way, we might confuse “reduce” with “map”. However, in “map”, the output is an array of the same length as the input. By contrast, with “reduce”, the output of each iteration is remembered for the next time around. That is, the value of “total” in each iteration is the block’s result from the last iteration.

The initial value of “total”, in the first iteration, is the parameter value that we pass, which is 0 in this case. If you don’t pass a parameter, then “total” is initialized with the first element of the enumerable, and the first iteration (i.e., the first application of the block) takes place on the second element. This is fine in the above example, but depending on the output you want, failing to pass a parameter, or passing one of the wrong type, can make a big difference.

You can also think of “reduce” as a sort of “join”, but one that evaluates its inputs and operations. So instead of getting the string “1+2+3+4+5”, you get the result of actually invoking 1+2, and then (1+2)+3, and then ((1+2)+3)+4, and then finally (((1+2)+3)+4)+5. This is why some Lisp versions call this “fold”, rather than “reduce”. I still don’t quite get why Smalltalk people call it “inject”, and thus never use that term in Ruby (except when introducing the five rhyming functional methods — select, detect, collect, inject, and reject — because it’s so much fun to say). But the effect, once you internalize it, can be used in many interesting ways.

Python doesn’t have a “reduce” method on sequences, but does have a builtin “reduce” function that can be invoked on sequences. (In Python 3, the “reduce” function was moved to the “functools” module — which is better than the fate Guido had originally planned for it.) Python’s “reduce” is similar to the one in Ruby. To sum numbers, we say:

As you can see (I hope), the use of “lambda” to create an anonymous function is analogous to the use of a block in Ruby. In Python’s “reduce” function, you first pass the function you wish to invoke on the sequence, and then the sequence itself. If you wish to pass an initial value for “total”, you can do so with an optional third parameter:

>>> reduce(lambda total, current: total + current, numbers, 10)
55

The classic use of “reduce” is to sum integers, as we saw above. But we can, of course, perform additional types of operations, and produce additional types of output. And to be honest, that’s where “reduce” starts to get more intriguing. Any operation that you want to perform on an enumerable, such as an array, set, or range, and apply cumulatively to its elements, makes for a good choice for “reduce”. By experimenting with the input enumerable, the initial value of “total” that we pass as a parameter, and the block, we can do many interesting things.

In coming posts, I’ll explore some more of these ideas, and give you a tour of “reduce” in both Ruby and Python that will hopefully open your eyes to some of them, and give you a sense of where “reduce” can help to improve your thinking, and your code.

Several months ago, I was teaching an introductory Python course, and I happened to mention the fact that I use Git for all of my version-control needs. I think that I would have gotten a more positive response if I had told them that my hobby is kicking puppies.

The reactions were roughly — and I’m not exaggerating here — something like, “What? You use Git?!? That so-called version control system whose main feature is eating our files?!?” And I got this not just from one person, but from all 20-something people who were taking my Python course. The more experience they had with Git, the more violently negative their reactions were.

I managed to calm them down a bit, and tried to tell them that Git is a wonderful system, except for one little problem, namely the fact that its interface is very hard to understand. But, I promised them, once you understand how Git works, and once you start to work with it within the context of understanding what it’s doing, things start to make sense, and you can really enjoy and appreciate the system.

I should note that since that Python class, I’ve returned to the same company to give two day-long Git classes. Based on the feedback I received, the Git class was very helpful, and I’m guessing that this is because I concentrated on what Git is really doing, and how the commands map to those actions. I’m pretty sure that people from that class are starting to appreciate the power and flexibility of Git, rather than focusing only on their frustrations with it.

However, my experience working with and teaching Git have taught me a great deal about designing both software and UIs. We love to say and think that excellent products with terrible marketing never get anywhere. And in the commercial world, that might well be true. Everyone loves to quote the movie “Field of Dreams” (which I never really liked anyway), and how the main character builds a baseball field after repeatedly hearing, “If you build it, they will come.” As numerous other people have said, this is not the case for businesses: If you build it, they probably won’t come, unless you’ve invested time and money in marketing your product.

However, in the open-source world, we expect to invest time in learning a technology, and are generally more technical folks in any event. Thus, we tend to be more forgiving of bad UIs, focusing on features rather than design. It’s thus possible for something brilliant, efficient, flexible, and profoundly frustrating for new users to become popular. Git is a perfect example of this.

Now, I happen to think that Git is one of the most brilliant pieces of software I’ve ever seen. Really, it’s impressively designed. However, the commands are counter-intuitive for many people who used other version-control systems, and it’s possible to get yourself into a situation from which an expert can extract himself or herself, but in which a novice is completely befuddled. Once you understand how Git works (brilliantly described in this video), things start to make sense. But getting to that point can take a great deal of time, and not everyone has that time.

In open source, then, “If you build it, they will come” might sometimes work. However, even if they do come, and even if they use the software that you have written, you might end up in a particularly unenviable situation: People will use the software, but will hate you for the way in which you designed it.

The upshot, then, is that it’s worth taking a bit of time to think about your users, and how they will use your system. It’s worth taking the time to create an interface (including commands) that will make sense for people. Look at WordPress, for example: It packs in a great deal of functionality, but also pays attention to the UI… and as a result, has become a hugely dominant part of the Web ecosystem.

Sure, Git is famous and popular, and I’m one of its biggest fans, at least in terms of functionality. But if Linus had spent just a bit more time thinking about command names, or behaviors, I think that we would have had an equally powerful tool, but with fewer people in need of courses to understand why their files are getting trampled.

If there’s anything that software people know, it’s that changing one part of a program can result in a change in a seemingly unrelated part of the program. That’s why automated testing is so powerful; it can show you when you have made a mistake that you not only didn’t intend, but that you didn’t expect.

If unexpected results can happen in a system that you control and supposedly understand, it’s not hard to imagine what happens when the results of your changes involve many pieces of software other than yours, running on computers other than yours, being used by customers who aren’t yours.

This would appear to be the situation with one of the latest anti-spam and security features for e-mail, known as DMARC.

I’m not intimately familiar with this standard, but I’ve seen other standards relating to e-mail in the past to know that anything having to do with e-mail will be frustrating for some of the people involved. E-mail is in use by so many people, on so many computers, and by so many different programs, that you can’t possibly make changes without someone getting upset. Nevertheless, the DMARC implementation and rollout by a number of large e-mail providers over the last few weeks has been causing trouble.

Let me explain: DMARC promises, to some degree, to reduce the amount of spam that we get by verifying that the sender’s e-mail address (in the “From” field) matches the server from which the e-mail was sent. So if you get e-mail from me, with a “From” address of “reuven@lerner.co.il”, DMARC will verify that the e-mail was really sent from the lerner.co.il server. To anyone who has received spam, or fake messages, or illegal “phishing” messages, this sounds like a great thing: No longer will you get messages from your friend with a hotmail.com address, asking for money now that they’re stranded in London. It really, admirably aims to reduce the number of such messages.

How? Very simply, by checking that the “From” address in the message matches the server from which the message was sent. If your DMARC-compliant server receives e-mail from “reuven@lerner.co.il”, but the server was some anonymous IP address in Mongolia, your server will refuse to receive the e-mail message.

So far, so good. But of course, for every rule, there are exceptions. Consider, for example, e-mail lists: When someone posts to a list, the “From” address is preserved, so that the message appears to be coming from the sender. But in fact, the message isn’t coming from the sender. Rather, it’s coming from the e-mail program running on a server.

For example, if I (reuven@lerner.co.il) send e-mail to a mailing list (list@example.com), the e-mail will really be coming from the example.com server. But it’ll have a “From” address of reuven@lerner.co.il. So now, if a receiver is using DMARC, they’ll see the discrepancy, and refuse to receive the e-mail message.

If lerner.co.il is using DMARC in the strictest way possible, then reuven@lerner.co.il sending to list@example.com will have especially unpleasant consequences: lerner.co.il will refuse to receive its own subscriber’s message to the list, because DMARC will show it to be a fake. These refusals will count as a “bounce” on the mailing list, meaning a message that failed to get to the recipient’s inbox. Enough such bounces, and everyone at lerner.co.il will be unsubscribed.

Yes, this means that if your e-mail provider uses DMARC, and if you subscribe to an e-mail list, then posting to such a list may result (eventually) in every other user of your provider being unsubscribed from the list!

I’ve witnessed this myself over the last few weeks, as members of a large e-mail list I maintain for residents of my city have slowly but surely been unsubscribed. Simply put, any time that a Hotmail, Yahoo, or AOL users posts to the list for Modi’in residents, all of these companies (and perhaps more) refuse the message. This refusal increases the number of bounces attributed to the users, and eventually results in mass auto-subscriptions.

As if that weren’t bad enough (and yes, it’s pretty bad), people who have been passively reading (i.e., not participating) in the e-mail list for years are now getting cryptic messages from the list-management software, saying that they have been unsubscribed because of excessive bounces. Most people have no idea what this means, which in turn leads to the list managers (such as me) having to explain intricate e-mail policy issues.

There are some solutions to this problem, of course. But they’re all bad, so far as I can tell, and came without any serious warning or notification. And when it comes to e-mail, you really don’t want to start rejecting message en masse without warning. The potential solutions are:

Subscribers can receive the digest mode of the list, which is always “From” an address on the server. If you get the digest, this problem won’t happen to you. If you are a mailing-list subscriber, rather than a list administrator, this is really the only recourse that you have.

The list managers can change the list such that instead of each message being “From” the individual, it’ll come from the list’s address. I know that there are some people who say that this is the right behavior for e-mail lists, but I have long subscribed (so to speak) to the school of thought that you don’t want to change the “From” address. (For more on this subject, you can read “reply-to considered harmful” and its associated messages.)

Supposedly, Mailman (the list-management software that I use) now has some support for DMARC that might solve the problem. But the more I learn about DMARC, the less I’m convinced that Mailman can do anything.

And by the way, it’s not just little guys like me who are suffering. The IETF, which writes the standards that make the Internet work, recently discovered that their e-mail lists are failing, too.

E-mail lists are incredibly useful tools, used by many millions (and perhaps billions) of people around the world. You really don’t want to mess with how they work unless there’s a very good reason to do so. Yes, spam and fraud are big problems, and I welcome the chance to change them.

But really, would it have been so hard to contact all of the list-management software makers (how many can there be?) and work out some sort of deal? Or at least get the message out to those of us running lists that this is going to happen? I have personally spent many hours now researching this problem, and trying to find a solution for my list subscribers, with little or no success.

This all brings me back to my original point: The intentions here were good, and DMARC sounds like a good idea overall. But it is affecting, in a very negative way, a very large number of people who are now suddenly, and to their surprise, cut off from their friends, colleagues, workplaces, and organizations. The fact that AOL and other e-mail providers are saying, “Well, you’ll just need to reconfigure your list software,” without considering whether we want to do this, or whether e-mail lists really need to change after more than two decades (!) of working in a certain way, is rather surprising to me. I’m not sure if there’s any way back, but I certainly hope that this is the last time such a drastic, negative solution is foisted on the public in this way.

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I’ve been using rvm for many years, and love it. Yes, I know that it rewrites simple commands, such as “ruby” and “gem”, so that I can use lots of different Ruby versions. Yes, I know that it can be overkill for certain situations. And yes, I know that rbenv is preferred by many.

But I’ve been using rvm for a long time, and I find it works very well for my needs. I can (and do) have many different versions of Ruby running on my computer, and having access to all of them at once is terrific.

I tend to be obsessive about updating Ruby gems on my systems, and I’m sure I’m not the only Rubyist who runs “gem update -V” (and yes, I love the “verbose” option) at least once per day. Updating gems never removes the old versions, and if you’re using Bundler in your Rails or Sinatra application, then it doesn’t really matter how many versions you have on your system. (And yes, I know that willy-nilly updating all gems on my system is probably not wise. If only that were the most foolish thing I do…)

The thing is, when I update gems, I do so in a particular version of Ruby. So even though I’m always running “gem update -V”, I never quite remember which versions of Ruby have the latest gems, and which haven’t been updated in a while. There is, of course, a clear correlation between the frequency with which I use a Ruby version and the freshness of the gems for that version on my system. But I sometimes find myself having to update gems in a version of Ruby that I haven’t used in a while.

So you can imagine my delight when I discovered “rvm do”. This is an rvm command that lets you execute a command in any or all of the Ruby versions installed on your system. It basically switches to the Ruby version and then executes the requested shell command — so you’re not executing a Ruby program in each separate version, but rather you’re executing a command-line program once for each version of Ruby installed. You can think of it as executing the same shell command once for each installed version, prefaced by “rvm VERSION_NUMBER”.

So, how can I ensure that all of the gems, for all versions of Ruby, are up to date? Very simply, I write:

rvm all do gem update -V

And if I want to check out some Ruby code, and see how it runs in all of the versions on my system, I can say

rvm all do ruby test.rb

If I just want to see the difference between doing something in 1.8, 1.9, 2.0, and 2.1 (without all of the patchlevels for 1.9.3), then I can just say:

rvm 1.8.7,1.9.3,2.0,2.1 do ruby test.rb

I’m already loving this feature, and can easily imagine cases — such as when teaching Ruby programming, and trying to show them the differences between versions — when this will be quite handy.

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In the wake of my last blog post, I’ve been thinking a great deal about the practice of teaching, and specifically the practice of teaching programming. I’ve realized that while instruction in programming is increasingly popular and important, the people engaged in such instruction aren’t comparing notes, learning from one another, or generally working to improve the trade.

I’ve decided to try to change that. I’ve created a new site, Teaching to Code, a discussion forum aimed at anyone who teaches programming to others. Whether you teach in person, produce screencasts, or lecture at the university level, I’m sure that there are techniques, ideas, and suggestions that you can share with other people, and which can help to improve the craft of teaching programming.

It’s true that many of us in this community are commercial instructors. As a result, there will undoubtedly be some overlap and competition among the people who participate. I’m optimistic that we can balance these competitive instincts and realities with the goal that we all (presumably) have, namely to improve our students’ knowledge and understanding of programming in general, and of the technologies we teach in particular.

In addition to general discussion on a variety of topics, I’m also aiming to have a monthly book/journal club. Each month, we’ll discuss a book, journal article, or blog post (or even a video, I guess) that can inform and improve our teaching. Some of the initial suggestions will come from readings I’ve had in graduate school; there were a number of papers that have really influenced my thinking, and that I believe will be interesting and useful for others, too. But I know that I’ve only read a minority of things written on this subject, and would be delighted to read and then discuss these items, as well.

If you’re a programming instructor of any sort, please join us! Contribute to the fledgling discussion, and suggest how we can make it better. If there is something that you feel could help you, or improve your teaching, then you can either ask on the forum or e-mail me at reuven@lerner.co.il. Either way, I hope that Teaching to Code will become a community of practice for programming instructors worldwide, helping teachers and students alike.

Several weeks ago, my wife and I saw a wonderful play at our local theater in Modi’in (“Mother Courage and Her Children“). At the end, the actors came out to receive their richly deserved applause. Three times, the actors came out, took their bows, and were warmly applauded by the audience. We loved their performance — but just as importantly, they loved performing, and they loved to see and hear the reactions from the audience, both during and after the play.

I’m sure that some or all of these actors have worked in television and the movies; Israel is a small country, and it’s hard for me to believe that actors can decide only to work in a single medium. But I’ve often heard that actors prefer to work on stage, because they can have a connection with the audience. When they say something funny, sad, or upsetting, they can feel (and even hear) the audience’s reaction.

But while we often hear about TV and movie stars making many millions of dollars off of their work, it’s less common for stage actors to make that kind of money. That’s because when you act on stage, you’re by definition limiting your audience to the number of people who can fit in a theater. Even the largest theaters aren’t going to hold more than a few hundred seats; by contrast, even a semi-successful TV show or movie will get tens or hundreds of thousands of viewers on a given night. (And yes, TV and film have many more expenses than plays do — but the fact remains that you can scale up the number of TV and film viewers much more easily than you can a play. Plus, movies and TV can both be shown in reruns.)

Another difference is the effort that you need to put into a stage production, as opposed to a TV program or a movie: In the former case, you need to perform each and every night. In the latter, you record your performance once — and yes, it’ll probably require multiple takes — and then it can be shown any number of times in the future. You can even be acting on stage while your TV show is broadcast. Or more than one of your movies can be shown simultaneously, in thousands of cities around the world.

What does this have to do with me? And why have I been thinking about this so much over the last few weeks, since seeing that play?

While I’m a software developer and consultant, I also spend a not-insignificant time teaching people: In any given week, I will give 2-4 full days of classes in Python, Ruby, Ruby on Rails, PostgreSQL, and Git, with other classes likely to come in the next few months.

I’m starting to dip my toes into the waters of teaching online, and hope to do it increasingly frequently over the coming months and years. But unlike most online programming courses currently being offered, I intend to make most or all of my courses real-time, live, and in person.

This has some obvious disadvantages: It means that people will need to be available during the precise hours that I’m teaching. It means that the course will have to be higher in price than a pre-recorded video course, because I cannot amortize my time investment over many different purchases and viewings. And it means that the course is limited in size; I cannot imagine teaching more than 10 people online, just as I won’t teach an in-person class with more than 20 people.

Given all of these disadvantages, why would I prefer to do things this way, live and in person?

The answer, in a word, is: Interactions.

I’m finishing my PhD in Learning Sciences, and if there’s anything that I have gained from my studies and research, it’s that personal interactions are the key to deep learning. That’s why my research is all about online collaboration; I deeply believe that it’s easiest and best to learn when you speak with, ask questions of, challenge, and collaborate with others, ideally when you’re trying to solve a problem.

I’m not saying that it’s impossible to learn on your own; I certainly spend enough hours each week watching screencasts and lectures, and reading blog posts, to demonstrate that it’s possible, pleasurable, and beneficial to learn in these ways. But if you want to understand a subject deeply, then you should communicate somehow with other people.

That’s one of the reasons why pair programming is so helpful, improving both the resulting software and the programmers who engage in the pairing. That’s why open source is so successful — because in a high-quality open-source project, you’ll have people constantly interacting, discussing, arguing, and finally agreeing on the best way to do things. And that’s why I constantly encourage participants in my classes to work together when they’re working on the exercises that I ask them to solve: Talking to someone else will help you to learn better, more quickly, and more deeply.

I thus believe that attending an in-person class offers many advantages over seeing a recorded screencast or lecture, not because the content is necessarily better, but because you have the opportunity to ask questions, to interact with the teacher, to clarify points that weren’t obvious the first time around, and to ask how you might be able to integrate the lectures into your existing work environment.

So for the students, an in-person class is a huge win. What do I get out of it? Why do I prefer to teach in person?

To answer that, I return to the topic with which I started this post, namely actors who prefer to work on stage, rather than on TV and in movies. When I give a course, it’s almost like I’m putting on a one-man show. Just as actors can give the same performance night after night without getting bored, I can give the same “introduction to Python” course dozens of times a year without tiring of it. (And yes, I do constantly update my course materials — but even so, the class has stayed largely the same for some time.) I’m putting on a show, albeit an interactive and educational one, and while I put on the same show time after time, I don’t get tired of it.

And the reason that I don’t get tired of it? Those same interactions, which are so beneficial to the students’ learning and progress, are good for me, as the instructor. They keep me on my toes, allow me to know what is working (and what isn’t), provide me with an opportunity to dive more deeply into a subject that is of particular interest to the participants, and assure me that the topics I’m covering are useful and important for the people taking my class.

I live and work in Israel, and one of the things that I love about teaching Israelis is that I’m almost guaranteed to be challenged and questioned at nearly ever turn. Israelis are, by nature, antagonistic toward authority. As a result, my lectures are constantly interrupted by questions, challenges, and requests for proof.

I have grown so accustomed to this way of things, that it once backfired on me: Years ago, I gave a one-day course in the US that ended at lunchtime — it turns out that the Americans were very polite and quiet, and didn’t ask any questions, allowing me to get through an entire day’s worth of material in just half of the time. I have since learned to make cultural adjustments to the number of slides I prepare for a given day, depending on where I will be teaching!

When I look at stage actors, and see them giving the same performance that they have given an untold number of times in the past, I now understand where they’re coming from. For them, each night gives them a chance to expose a new audience to the ideas that they’re trying to get across through their characters and dialogue. And yes, they could do that in a movie — but then they would be missing the interactions that they have with the audience, which provide a sense of excitement that’s hard to match.

Does this mean that I won’t ever record screencasts or lectures? No, I’m sure that I will do that at some point, and I already have some ideas for doing so. But they’ll be fundamentally different from the courses that I teach, complementing the full-length courses, rather than replacing them. At the end of the day, I get a great deal of satisfaction from lecturing and teaching, both because I see that people are learning (and thus gaining a useful skill), and because my interactions with them are so precious to me, as an instructor.

It has been many years since Python developers were really supposed to worry about new-style vs. old-style classes. There is only one style (new) in Python 3.x, and even in Python 2.x, old-style classes have not been recommended for many years. Nevertheless, I mention old-style classes in my Python courses, mostly so that participants will understand the potentially serious implications of creating classes without inheriting from object. For example:

The above is the way that modern Python programmers define classes. This is the preferred way, for sure; if you’re writing old-style classes, then you’re almost certainly doing something wrong. But it’s so easy to create an old-style class in Python — all you have to do is forget to inherit from “object”:

As you can see, the fact that I created an old-style class directly affects the types of objects that I have created, and thus their capabilities. For many years, it has been seen as a mistake to create old-style classes; not only are you missing out on new functionality, but you are creating objects that behave differently from the rest of objects in Python.

I was just teaching a Python class at a company that has a fair amount of legacy Python code. It turns out that this legacy code includes a large number of old-style classes. The company asked me whether it was worth upgrading all of their old-style classes to use new-style classes; my answer was that (1) if it ain’t broke, don’t fix it, (2) it’s hard to know whether the upgrade would be trivially easy or impossibly hard, and (3) you’ll likely want to upgrade these classes over time, doing so incrementally.

Someone then asked me whether there is a performance difference between old-style and new-style classes, in order to evaluate the importance of doing such an upgrade project. I had to admit that I wasn’t sure, and couldn’t find anything online (after doing a quick search) on the subject. I thus decided to do a small benchmark to see what might be faster (or slower). I’m not an expert in benchmarking, but I did want to check the basic speed of (1) object creation, (2) inheritance, and (3) implementation of __repr__.

The results surprised me: New-style classes are substantially faster. Here is the benchmark that I ran on the new-style class:

My test of old-style classes was precisely the same, except that I omitted “object” between the parentheses in the class definition of Person.

I used %timeit from within IPython to run the function 100,000 times for each of the two versions (old-style and new-style). The results surprised me: Old-style classes took 3.09 µs per iteration, while new-style classes took 2.44 µs per iteration, a difference of more than 20 percent!

The bottom line would seem to be that if you’re running large systems in Python and are still using old-style classes, it’s not just worth upgrading to new-style classes for reasons of aesthetics, features, and compatibility. It’s also going to speed up your code, particularly if you have a large, long-running system that invokes lots of methods.

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When I teach a Ruby or Python class, I always begin by going through the various data types. My students are typically experienced programmers in Java, C++, or C#, and so it no longer surprises me when I begin to describe numbers, and someone asks, “How many bits is an integer?”

My answer used to be, “Who cares?” I would then follow this with a demonstration of the fact that in these languages, numbers can be pretty darned big before you have to worry about such things.

But over the last few months, I’ve begun to understand the reason for this question, and others. Indeed, I have begun to understand one of the reasons why dynamic languages can be so difficult for people to learn after they have worked with a static language.

Let’s take a simple example. In a typical, C-style statically typed language, you don’t just assign a variable. You must first declare it with a type. You can thus say something like this:

int x;
x = 5;

In both Ruby and Python, you can do something similar:

x = 5 # no type declaration needed

On the face of it, these seem to be doing similar things. But they aren’t.

In a static language, a variable is an alias to a place in memory. Thus, when I say “int x”, I’m telling the compiler to set aside an integer-sized piece of memory, and to give it an alias of “x”. When I say “x = 5”, the compiler will stick the number 5 inside of that int-sized memory location. This is why static languages force you to declare types — so that they can allocate the right amount of space for the data you want to store, and so that they can double-check that the type you’re trying to store won’t overflow that allocated area.

Dynamic languages don’t do this at all. Whereas assignment in a static language means, “Put the value on the right in the address on the left,” assignment in a dynamic language means, “As of now, the name on the left points to the object on the right.”

In other words, assignment in a dynamic language isn’t really assignment in the traditional sense. There’s no fixed memory location associated with a variable. Rather, a variable is just a name in the current scope, pointing to an object. Given that everything in both Python and Ruby is an object, you never have to worry about assignment not “fitting” into memory.

This is also why you can say “x = 5” and then “x = [1,2,3]” in a dynamic language: Types sit on the data, not on the variable. As long as a variable is pointing to an object, you’re just fine, because all object pointers are the same size.

The bottom line, then, is that = in static languages and = in dynamic languages would seem, on the surface, to be doing similar things. But they’re definitely not. Once you understand what they are doing — putting data in memory, or telling a name to point to a value — many other mysteries of the language suddenly make more sense.

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I have been consulting, developing, and offering training classes in both Ruby and Python for a number of years now — more than 15 years in Python, and more than 7 years in Ruby. Inevitably, when someone from one of my courses hears that I use more than one language, they ask me, “So, which one do you prefer?”

One way to address this is to speak like a parent (which I am), and to give the analogy that just like I love all three of my children equally but differently, I love these two languages equally, but differently. But the most recent time I was answering this question, I asked myself, how do you like them differently? What is appealing about each of these languages? Why do you enjoy working with (and teaching) both of them?

I began to search for analogies that would describe the relationship between Ruby and Python, and the reason why I enjoy working with them both. I would sometimes extend the children analogy, saying that they’re like siblings. But beyond the fact that I’m not their parent, I decided that there were enough differences to make the sibling analogy not quite appropriate. Perhaps it would be most appropriate to call them cousins, or even second cousins.

But then I hit upon another analogy, one which might indicate my age and television-watching habits as a child, but which I think is somewhat apt: The Odd Couple.

I remember the Odd Couple as an American sitcom from the 1970s, broadcast in endless reruns on certain stations, in which two divorced men become roommates and friends, despite their with wildly different habits and outlooks on life. (I should note that the Neil Simon play and movie, upon which the TV series was based, is far darker, and really surprised me when I saw it after years of watching the TV show.)

The viewers aren’t ever expected to prefer neatnik, uptight Felix or sloppy, happy-go-lucky Oscar, but rather to appreciate the differences between the two, and to see a bit of themselves in each character. In some ways — and perhaps more philosophically than was ever intended — the play, movie, and show are there to tell us that there is no one “right” way to approach life, and that each has its advantages and disadvantages. Balance is the key.

The more I think about it, the more I like this analogy, because it speaks to the differences between the languages, and the reasons why I love to work in each of them. Python, not surprisingly, is Felix: It’s clean, crisp, elegant, and engineered precisely. It’s no surprise that Python has been called “executable pseudo-code,” in that I’ve met a very large number of people (many of whom take my courses) who have been working with Python for months without knowing precisely what they were doing.

Python is conservative by nature, and that has served the language well for more than two decades. Indeed, you could argue that the entire 2-to-3 Python upgrade issue, which has been causing ripples of late, is the result of Python betraying this conservative culture, and making a clean break with past versions for the first time in its history. There are parts of Python that drive me crazy, such as len being a builtin function, list.sort not returning a value, the limits on lambda. the need for both tuples and lists, and the way that super works. But every language has its issues, and a very large number of them were improved or removed altogether in Python 3.

But other parts of the language are beautiful, such as the way in which operator overloading is done. Sure, Ruby lets you rewrite + directly, but I think that there’s something about Python’s __add__ which tells newcomers that they should avoid messing with it until they know what they’re doing. I have also grown to love list comprehensions (as well as dictionary and set comprehensions), even though I readily admit that the syntax is difficult for beginners. Also, the Python standard library is just a joy to work with; you can really depend on things working pretty well. And one of the things that people hate at first about Python, namely the required whitespace, is sheer genius in my book. Decorators are also wonderful; while I don’t use them much, they are an elegant and powerful way to intercept function and class definitions, and do all sorts of wild stuff with them.

Ruby, on the other hand, is Oscar: It’s infinitely flexible, messy, and creative — but it works the way you want it to work. Ruby inherited many of the characteristics of Perl, which Larry Wall deliberately meant to be close to natural human language. Sure, it’s a minor miracle that Ruby’s syntax can be described using computers, given its complexity, but that complexity allows me flexibility, creativity, and intellectual excitement that I can’t get elsewhere. Add blocks to the mixture, and you have a language which gives you raw building blocks that allow you to solve problems quickly, easily, and naturally, with less code than would otherwise be necessary. For example, ActiveRecord might have its problems, but I generally love its API and the magic that it performs on my behalf. The way that validations and associations look like declarations (but are actually class methods) is great, making for readable code.

Of course, Ruby has its problems, as well: The object model is elegant and simple — but nearly impossible for newcomers to the language to grasp. (I should know, I teach quite a lot of them.) The fact that everything ends with “end” drives me a bit crazy. So do the differences between procs, lambdas, and blocks. And the “stubby lambda” syntax. But again, every language has its issues and trade-offs, and the ones that Ruby has made are more than reasonable for my work.

Matz has said that Ruby was optimized for programmer happiness, and Avdi Grimm has used the word “joy” to describe programming in Ruby — and I have to agree with both of them. Programming in Python feels more like solving a puzzle, but programming feels more satisfying; I’m unleashing my creative energies, and using the language to solve problems in the way that I want. Python is crisp and demanding, and Ruby is messy and fun. You know, like Felix and Oscar.

Of course, the style of the languages might be very different — but at the end of the day, there’s a lot of overlap between the two. IPython and Pry, PyPi and RubyGems, dicts and hashes, “def initialize” and “def __init__” — if you know Ruby, then learning Python isn’t very difficult, and vice versa. Both are byte compiled, interpreted, object-oriented, strongly typed, dynamic languages. Both have a GIL, which drives people crazy with threading. Both make reflection and metaprogramming easy and natural. Both languages encourage modularization of code, with short functions. Both encourage you to test your code. Both have active open-source communities. And both can be used to solve lots of problems, easily and quickly.

Indeed, the languages are similar enough that I’ve often “stolen” ideas, examples, and exercises from my Python classes for my Ruby classes, and vice versa. And I’ve often thought, when reading the documentation for a method on a built-in Ruby class, that it’s a shame that there’s no Python equivalent… only to discover that there is.

I love Python’s PEP process, which makes it easy for the community to document and discuss changes to the language. And yet, somehow, Ruby has moved from version 1.9 to 2.0 to 2.1 in the last few years, with great improvement on all fronts, without such a clear-cut process. I’m not quite sure how Ruby manages to do it, but it does, and rather impressively.

So, which do I prefer? For Web development, I use Ruby (and Rails or Sinatra). For small projects and problem solving, and sysadmin types of things, I use Python. If I had to do large-scale calculations, then NumPy would make Python a no-brainer. As a first programming language to teach young people, I think that Python is an almost perfect choice. And for mind-twisting, understand-how-languages-work examples, Ruby beats everyone hands down.

At the end of the day, I’m happy to have a foot in each camp, and to be comfortable with both. Because sometimes you want to be Felix, and sometimes you want to be Oscar, and it’s always nice to have to choose between the two.